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Record W2961801132 · doi:10.1021/acsomega.9b00863

Charge-Free Mixing Entropy Battery Enabled by Low-Cost Electrode Materials

2019· article· en· W2961801132 on OpenAlex
Meng Ye, Mauro Pasta, Xing Xie, Kristian L. Dubrawski, Jianqaio Xu, Chong Liu, Yi Cui, Craig S. Criddle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueACS Omega · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsnot available
FundersDivision of Engineering Education and CentersStanford UniversityNatural Sciences and Engineering Research Council of CanadaStanford Woods Institute for the EnvironmentTomKat Center for Sustainable Energy, Stanford UniversityFondazione Oronzio e Niccoló De Nora
KeywordsSeawaterElectrodeMaterials scienceBattery (electricity)VoltageCoatingEnergy storageEffluentEnvironmental scienceChemical engineeringElectrical engineeringEnvironmental engineeringChemistryNanotechnologyPower (physics)EngineeringOceanographyPhysicsThermodynamicsGeology

Abstract

fetched live from OpenAlex

Salinity gradients are a vast and untapped energy resource. For every cubic meter of freshwater that mixes with seawater, approximately 0.65 kW h of theoretically recoverable energy is lost. For coastal wastewater treatment plants that discharge to the ocean, this energy, if recovered, could power the plant. The mixing entropy battery (MEB) uses battery electrodes to convert salinity gradient energy into electricity in a four-step process: (1) freshwater exchange; (2) charging in freshwater; (3) seawater exchange; and (4) discharging in seawater. Previously, we demonstrated a proof of concept, but with electrode materials that required an energy investment during the charging step. Here, we introduce a charge-free MEB with low-cost electrodes: Prussian Blue (PB) and polypyrrole (PPy). Importantly, this MEB requires no energy investment, and the electrode materials are stable with repeated cycling. The MEB equipped with PB and PPy achieved high voltage ratios (actual voltages obtained divided by the theoretical voltages) of 89.5% in wastewater effluent and 97.6% in seawater, with over 93% capacity retention after 50 cycles of operation and 97-99% over 150 cycles with a polyvinyl alcohol/sulfosuccinic acid (PVA/SSA) coating on the PB electrode.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.223
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it